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Healthcare Staffing · B2B
AI-Assisted Travel Nurse Recruitment Platform
The AI does the reading. Recruiters do the deciding. Most of this project was working out exactly where that line sits.
Role
Product Designer
PLatform
B2B Enterprise Web App
Status
Shipped (2025)
Industry
Healthcare Staffing
Project Overview
FlexCare is an AI-powered recruitment platform built for healthcare staffing agencies to streamline the hiring of travel nurses. By automating candidate qualification, credential verification, and intelligent job matching, it enables recruiters to focus on faster, more confident hiring decisions while retaining full control over the recruitment process.
Problem
Recruiters spent hours manually reviewing applications, validating licenses, and comparing candidates across multiple systems. This repetitive process slowed hiring and made it difficult to scale recruitment.
Solution
Designed an AI-assisted recruitment workflow that automates candidate intake, credential validation, intelligent job matching, and recruiter insights while keeping every hiring decision human-led.
Results
A workflow built to collapse manual verification into a single review step, replace one opaque score with an inspectable one, and give recruiters a ranked shortlist instead of a spreadsheet.
The Challenge
Healthcare staffing is a race against time. Recruiters often manage hundreds of travel nurse applications while juggling license verification, credential checks, job matching, and candidate communication. Most of this work is repetitive and manual, leaving less time for evaluating the right candidates.
The challenge wasn't access to information. It was turning fragmented information into confident hiring decisions.
Process
One point of contact, and a deadline.
The project ran over two weeks with the client's Product Manager as the only stakeholder. He shared the requirements, explained the healthcare domain, and validated decisions through the existing PRD.
Without access to recruiters, I researched AI patterns across recruitment platforms outside healthcare to understand what had become standard and what still needed explanation. That informed features like confidence scoring and explainability, while keeping the solution aligned with the existing product architecture.
Constraints
One stakeholder throughout the project.
No direct access to recruiters or end users.
Cross-industry pattern research instead of formal user research.
Product decisions validated through the Product Manager.
Where AI Adds Value
Instead of replacing recruiters, AI supports them throughout the recruitment journey by handling repetitive tasks and surfacing insights before human review.
Extracts and structures candidate information
Generates AI-powered candidate summaries
Provides transparent scoring to support recruiter decisions
Validates licenses and credentials
Recommends best-fit candidates for open roles
Design Goal
Reduce repetitive analysis while preserving recruiter accountability.
Automation trade-offs
How much automation, function by function
The question was never whether the AI should do a thing. It was how much of it, and what the recruiter got back in exchange. I made those calls myself. The only thing I took to the PM was whether something could be built inside the architecture they already had.
From application to submission
The AI does the reading at the front and the ranking in the middle. Every point where something actually happens to a nurse is a recruiter.
Open Jobs & AI Intake Queue
Recruiters start with a list of open travel nursing jobs showing key details such as priority, pay, duration, certifications, and facility. AI continuously identifies the strongest candidate matches based on specialty, location, pay, shift preference, licenses, and availability.
Selecting Review opens the AI Intake Queue, where recruiters can review AI-qualified candidates independently of specific jobs. Recruiters can then review a candidate and assign them to the appropriate job for submission.
Job & Candidate Matching
Review
Rather than reviewing resumes, certifications, and online profiles separately, recruiters can validate everything from one screen. AI summarizes the candidate's background, verifies available information, flags missing requirements, and organizes completed and pending validations.
Once the profile is fully reviewed, recruiters can confidently add the candidate to the Matching Pool, creating a shortlist of qualified candidates ready to be matched with suitable travel nursing jobs.
Approved Candidates
The Candidate Pool is the qualified list of candidates who have completed the AI intake and review process. These candidates are ready to be matched to open jobs and submitted for assignments.
Recruiters can open a candidate’s profile and review all relevant information in one place, including credential and license verifications, availability, previous assignments, feedback, quality scores, and overall experience. This gives recruiters a complete view of the candidate and helps them quickly determine whether the candidate is qualified and suitable for a job.
Once the candidate has been reviewed and finalized, the recruiter can move forward with the submission process.
Profile Submission
When the recruiter clicks Add to Job, a list of available jobs appears, showing key details such as role, facility, location, start date, pay, and priority. Recruiters can select a suitable job and submit the candidate directly.
Design Principles
Human-in-the-Loop AI
AI assists, recruiters decide.
Explainable AI
Recommendations are supported with transparent reasoning.
Reduce Repetitive Work
Automate operational tasks, not decision-making.
Decision-First Design
Every screen helps recruiters answer the next question quickly.
What I have instead of metrics
I moved to another project shortly after handoff, so I don't have adoption metrics or placement data.
What I do have is the client's feedback. After reviewing the platform, the FlexCare client said,
This is what I wanted.
The Product Manager called me afterwards to share how happy the client was with the design and the overall workflow.
Thank you!
